Study on Condition Monitoring of Power-Shift Steering Transmission Based on Support Vector Machine

Abstract

This paper is aimed at the condition monitoring problem of the Power-shift Steering Transmission (PSST), a method of multiple out least squares support vector regression is developed which is applied to prediction of spectrometric oil analysis data. Radial Basis Function (RBF) is used is this algorithm. There are two parameters γ and σ. The selection of γ and σ is studied using cross validation method with spectrometric oil analysis data. The prediction of spectrometric oil analysis data for PSST is done. A comparative analysis is made between predictive and actual values. The method has been proved that it has better accuracy in prediction, and any possible problem in PSST can be found through a comparative analysis which has important significance for preventing faults. Keywords-condition monitoring; Power-Shift Steering Transmission (PSST); Support Vector Machine (SVM)

6 Figures and Tables

Cite this paper

@article{Zhang2009StudyOC, title={Study on Condition Monitoring of Power-Shift Steering Transmission Based on Support Vector Machine}, author={Ying-feng Zhang and Biao Ma and Yuan Qin Zhu and Jin-le Zhang}, journal={2009 International Conference on Computational Intelligence and Software Engineering}, year={2009}, pages={1-4} }